Line-of-sight rates extraction of roll-pitch seeker under anti-infrared decoy state

In this paper,the method of extracting guidance information such as the line-of-sight(LOS)rates under the anti-infrared decoy state for the roll-pitch seeker is researched.Coordinate systems which are used to describe the angles transform are defined.The LOS angles reconstruction model of the roll-pitch seeker in inertial space is established.A Kalman filter model for extracting LOS rates of the roll-pitch seeker is proposed.In this model,the target performs constant acceleration(CA)model maneuvers.The error model of LOS rates extraction under infrared decoy state is established.Several existing methods of extracting LOS rates under anti-infrared decoy state are listed in this paper.Different from the existing methods,a novel method that uses extrapolated values of target accelerations as filter measurements is proposed to solve the guidance information extraction problem under the anti-infrared decoy state.Numerical simulations are conducted to verify the effectiveness of the proposed method under different target maneuvering models such as the CA model,the CA extended model and the singer model.The simulation results show that the proposed method of extracting guidance information such as LOS rates for the rollpitch seeker under the anti-infrared decoy state is effective.

SCKF-STF-CN:a universal nonlinear filter for maneuver target tracking

Square-root cubature Kalman filter (SCKF) is more effective for nonlinear state estimation than an unscented Kalman filter.In this paper,we study the design of nonlinear filters based on SCKF for the system with one step noise correlation and abrupt state change.First,we give the SCKF that deals with the one step correlation between process and measurement noises,SCKF-CN in short.Second,we introduce the idea of a strong tracking filter to construct the adaptive square-root factor of the prediction error covariance with a fading factor,which makes SCKF-CN obtain outstanding tracking performance to the system with target maneuver or abrupt state change.Accordingly,the tracking performance of SCKF is greatly improved.A universal nonlinear estimator is proposed,which can not only deal with the conventional nonlinear filter problem with high dimensionality and correlated noises,but also achieve an excellent strong tracking performance towards the abrupt change of target state.Three simulation examples with a bearings-only tracking system are illustrated to verify the efficiency of the proposed algorithms.